Process of spatial color restoration of an image

ABSTRACT

The process of the invention enables the spatial color alterations of a silver image to be taken into account according to one of its main axes (  19 ). The process of the invention enables the altered or faded colors of the silver image to be restored automatically, without depending on the skills of an operator to perform a color restoration treatment. A digital image ( 12 ) is divided into adjacent pixel strips ( 18 ), arranged perpendicular to the direction ( 19 ) according to which the color alteration occurs. For each of these strips ( 18 ), optical density distributions of each pixel are calculated and compared with reference optical density values. The process of the invention enables the automatic correction of all the strips ( 18 ) comprising the altered pixels, by applying a linear transformation enabling the transformation of the optical density values of the altered pixels, into the optical density values of a pixel strip of least degradation. The process of the present invention is used in the technological field of the restoration of color photographic images.

FIELD OF THE INVENTION

The present invention is in the technical field of imaging. The objectof the present invention is an automatic process of color restoration ofan image; after said color has been altered with regard to the originalcolor of the image.

BACKGROUND OF THE INVENTION

The renovation or restoration of color images recorded on silversupports is usually done by processing a digitized version of thesealtered silver images. The restoration of altered images enables, byvisual examination, the image to recover its original colors. Theconventional silver supports of the images generally comprisephotographic film or paper. In the following description, a silver imagemeans a color image obtained from silver halide photographic emulsions.The alteration or degradation of color images recorded on these silversupports is due for example to aging, or to the exposure of these silversupports to light sources, at the time of handling. Restorationprocesses of image colors, known to those skilled in the art, consistfor example in digitizing an image previously recorded on a silversupport (photographic film or paper), and then processing the digitizedimage in order to restore its colors. These restoration processesconsist in transforming the degraded colors on the digitized image, byusing the algorithms of image processing software.

The digital image, transformed by the processing, thus has restoredcolors that approximately match those of the original image.

U.S. Pat. No. 5,796,874 describes the restoration of images printed on amaterial support, for example paper type, discolored or faded over time.This patent describes a method and means that enable an operator withouta high level of skill, to easily restore an image whose colors have beenaltered. The operator in particular does not have to select and addfilters in the scanner used to digitize the image to be restored. But,the operator has to apply image degradation models over time to theimage to be restored. That is the restoration is done according to theselection of a time variable: for example, it is assumed that the imageis some ten years old and the restoration model for this time (some tenyears) is applied in order to restore the colors of the altered image.The restoration method enables a restoration model of the image colorsto be obtained and selected automatically, according to a time variableassigned to the image. The image restored in this way can be displayedon a monitor type screen. In addition, the operator can also selectanother model, linked to another time variable, if the first restorationresult was not satisfactory. The correction rule used is applieduniformly to the entire image.

The document of the University of La Rochelle, France, by M. Chambah andB. Besserer, entitled “Digital Color Restoration of Faded MotionPictures”, and presented to the first International CGIP Conference(Color in Graphics and Image Processing) in Saint-Etienne, France,October 1-4, 2000, describes a method of color restoration of fadedimages on old films. Firstly, the film is digitized with a scanner; thenthe coverage effect of the spectral densities of the various dyes issubtracted, by using an adjustment matrix. Secondly, the color channelsof the image are balanced using another correction matrix. Finally, thecontrast is increased to improve the visual quality. In this method, thecorrection rule used is applied uniformly to the entire image.

In an article (IEEE Transactions On Image Processing, Volume 9, No. 5,May 2000), entitled “Adaptive Image Contrast Enhancement UsingGeneralizations of Histogram Equalization”, J. Alex Stark describes amethod of contrast enhancement in an image. This method uses acumulative function of gray levels in a zone or a window (for examplewith square shape) around a pixel, without interdependence constraintbetween these zones. The corrections are independent for each imagerepresentation zone.

The restoration means of the prior art do not take into account thespatial variations of the alteration of colors in an image. The means ofthe prior art use mathematical models or functions that take intoaccount certain important parameters that influence the degradation ofthe colors of an image recorded on photographic film or paper, to thenrestore the colors of the entire image uniformly.

SUMMARY OF THE INVENTION

The process of the present invention, for the spatial restoration of thecolors of an altered image, enables, from the detection of alterationsor degradations of color that vary spatially from one edge to the otherof the image, color restoration according to the original colors of saidimage. The advantage of this invention process is to restoreautomatically, rapidly, and reliably the original colors of the image,whereas said colors had not been uniformly altered.

More particularly, the invention relates to an automatic process ofrestoration of the color of a silver image whose color is alterednon-uniformly with regard to the original color of the silver image,spatially in the plane of the silver image, and according to a directionparallel to one main axis of the image; this process comprises thefollowing steps:

-   -   a) digitize the altered silver image by using a measuring scale        of optical densities;    -   b) filter all the pixels of the digitized image;    -   c) divide the digital image into pixel strips arranged        perpendicular to the direction of the main axis of the image        according to which the color alteration occurs, the joining of        all the pixels of each strip representing all the pixels of the        digital image;    -   d) calculate, for each pixel strip, and for each of the color        channels forming the image, a distribution of the optical        densities of the pixels forming said strip;    -   e) calculate, for each of said distributions of step d), a top        crude reference value of optical density, and a bottom crude        reference value of optical density;    -   f) calculate, from all the top and bottom crude reference values        of step e), the corresponding top filtered reference values of        optical density and bottom filtered reference values of optical        density,    -   g) determine, from the top and bottom filtered reference values        of optical density of step f), top reference curves of optical        density and bottom reference curves of optical density, said        reference curves being representative of the color degradation        profile of the image;    -   h) determine, for each of the color channels forming the image,        and from the maximum value of optical density of the top        reference curve of optical density, the pixel strip of least        degradation;    -   i) apply to each pixel strip of the digital image other than the        pixel strip of least degradation, and to each of the color        channels forming the image, a linear transformation enabling the        transformation of the optical density filtered values placed on        the top reference curve and on the bottom reference curve of        optical density of said each pixel strip, respectively into top        and bottom values of optical density of the pixel strip of least        degradation.

The process of the invention enables a restored image to be obtained.One characteristic of the invention, which is shown by a major advantagewith regard to the prior art, is to take into account the non-uniformspatial variations of color having altered for example a silver image.This process enables the automatic restoration of the faded colors ofthe image, without bringing in the photographic skills of an operator.Another advantage of the process of the invention to execute colorrestorations of altered or faded images is the time saved, andconsequently increased productivity, with regard to manual treatment ofthe spatial restoration of images by an operator.

Other characteristics and advantages will appear on reading thedescription, with reference to the drawings of the various figures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 represents diagrammatically a color photographic film and itswinding means.

FIG. 2 represents diagrammatically a hardware environment used forexample to implement the invention process.

FIG. 3 represents diagrammatically a digitized image of the image to berestored.

FIG. 4 represents an example of the distribution, in a color channel, ofthe optical densities of a pixel strip of a digital image.

FIG. 5 represents diagrammatically, for a color channel, a developmentof the distribution of optical densities in the image, according to amain axis by which the color alteration occurs.

FIG. 6 represents diagrammatically an example of the diagram, in eachcolor channel, of spatial representations of the distribution of opticaldensities in the image filtered of its contents.

FIG. 7 represents the optical density restoration function.

FIG. 8 represents an example of the distribution of the cumulatedoptical densities of FIG. 4.

FIG. 9 represents a filtering principle of the image by following themaxima.

FIG. 10 represents diagrammatically, for a color channel, thedistribution of the optical densities after filtering of FIG. 5.

DETAILED DESCRIPTION OF THE INVENTION

The following description is a detailed description of the inventionwith reference to the drawings in which the same numerical referencesidentify the same elements in each of the different figures.

The process of the invention is used to automatically restore the colorsof an image whose color is altered, i.e. faded with regard to theoriginal color of the image. The images to be restored may be still oranimated. Still images are for example color photographs (portraits,landscapes, etc.). Animated images are for example sequences of motionpicture film. These images are recorded on silver photographic supports.The problem of the non-homogeneous alteration of the colors of imagesrecorded on a silver photographic support is found especially when,according to FIG. 1, these silver image supports 2 are wound on reels 1.A silver image support is for example a motion picture film recorded incolor. Over time or following uncontrolled temperature and/or hygrometryvariations, degradation of the dyes occurs. In practice, the degradationof the dyes of the image occurs more strongly on the edges 4F, 5F thanin the center of the film 2. The line showing the middle of the film 2and the silver images 3 is represented by a first main axis 6.

FIG. 2 shows a preferred hardware environment used to implement theinvention process interactively. An operator who wishes for example torestore one or more original images 3 whose colors have been alteredover time with regard to the original color, uses a terminal 7. Theterminal 7 is for example a personal computer or PC comprising akeyboard 8 and a display screen 11. The terminal 7 is interfaced with amouse 9 with at least one-control button 10. The operating system of theterminal 7 is for example Unix, Windows or Linux. All these operatingsystems are capable of recognizing peripherals such as a scanner ordigitizer 13, a printer 14, or any other device 15 connected to theterminal 7, and enabling the capture of images or image sequences. Theprocess of the invention enables the automatic digitization of thesilver image 3 whose colors are altered, by using for example thescanner 13. The digitized image 3 is encoded as digital values. Todigitize the image, a measuring scale of optical densities is used. Inother words, the digital values associated with each pixel, and for eachof the color channels forming the image, are proportional (linearfunction) to the optical densities. The image 3 is digitized in an image12 that can thus be viewed on the screen 11. The digital image 12 can besaved in an internal memory of the terminal 7.

In another embodiment, the implementation of the process of theinvention can also be non-interactive, and not necessarily use meanscomprising a display screen 11. In this embodiment, the process of theinvention is implemented by using a dedicated processor; i.e. aprocessor configured with ports and basic software functions enablingsaid process to be implemented. For example an FPGA processor is used(Field Programmable Gate Array). This processor is for exampleintegrated into the scanner 13, and automatically executes therestoration just after the digitization operation of the silver image 3.

The alteration, i.e. discoloration or fading of the colors of a silverimage is caused in particular by the exposure of the silver imagesupport to the light and/or humidity. Films are for example stored woundon reels 1; in these conditions, the alteration of the colors of thesilver image 3 recorded on the film 2 occurs first in the neighborhoodof the edges 4F, 5F of said film 2. Over time, color alteration is thusgreater in the neighborhood of the edges 4F, 5F of the film 2 wound onthe reel 1, than in that of the main axis 6 located in the center of thefilm 2. Consequently, a first assumption based on experimental results,and prior to the implementation of the process of the invention,consists in acknowledging on the one hand that the color alterationvaries spatially in the plane of the image 3, according to a directionperpendicular to the first main axis 6, or parallel to a second mainaxis 19 of the image 3, 12. Thus, the color alteration varies accordingto the distance with regard to the edges 4F, 5F of the film 2. On theother hand, this first assumption is linked to a second one thatconsists in also acknowledging that the color degradation is uniform(i.e. does not vary) according to the first main axis 6, parallel to theedges 4F, 5F. This assumption of the uniformity of color degradationmust be verified at least on the area of the image according to thismain axis 6.

According to the FIG. 3, and by analogy with the FIG. 1, the edges 16,17 of the digital image 12 (digitized image 3) correspond respectivelyto the edges 4I, 5I of the silver image 3. The edges 26, 27 of thedigital image 12 correspond to the two other edges of the silver image3, said other edges being parallel to the second main axis 19. The firstmain axis 6 is perpendicular to the second main axis 19. The two mainaxes 6, 19 of the image 3, 12 are cut at a point 20, which is placed inthe center of the image.

To determine the color density variations spatially in the plane of thedigital image 12 with regard to the original color of the correspondingsilver image 3, the algorithm of the process of the invention enablesthe pixel distributions to be calculated automatically, according totheir respective optical density encoded digital values, in a movingstrip 18 of the image 12. The process of the invention enables thesedistributions to be calculated in sections or strips 18 representativeof a part of the image 12. The width 21 of the strip 18 includes forexample five columns of pixels parallel to the axis 6. The length of thestrip 18 corresponds to the total extent of the image 12 according tothe direction of the axis 6, perpendicular to the direction of the axis19; the direction of the axis 19 characterizes the direction of thevariation of the color alteration. The total extent of the image 12 isthe image dimension: for example its height or width. In a particularembodiment of the invention, the least wide strip 18 is reduced to asingle row of pixels parallel to the axis 6.

FIG. 4 represents an example of the distribution of the opticaldensities of a pixel strip, in a given color channel, for example red. Acurve 22 represents the pixel distribution (number of pixels N accordingto the Y axis) according to the optical density encoded values V_(C)(DO)of said pixels (according to the X axis). The curve 22 represents, for agiven spatial position of the strip 18 in the plane of the image 12, thedistribution of the optical density encoded values V_(C)(DO) of thepixels forming said strip 18, between a minimum optical density valuerepresented by the point 23 and a maximum optical density valuerepresented by the point 24. Generally, the image is affected by noise(interference signal). The causes of noise can be multiple. In thecontext of the invention, unwanted noise is mainly due to dust. Dust forexample generated black spots in the image, or even white spots, and itdisturbs the distribution of the optical density encoded valuesV_(C)(DO). According to FIG. 4, the optical density encoded values ofblack spots are for example represented by a lobe 28, and opticaldensity encoded values of the white spots are for example represented bya lobe 29. The process of the invention enables the automaticelimination of these aberrant lobes 28, 29.

FIG. 8 represents an example of the curve 70 of the distribution of thecumulated optical densities of FIG. 4. According to a particularembodiment of the invention, the cumulated distribution of FIG. 8 is forexample divided into classes of equal numbers of pixels having valuesnear to the optical densities. Preferably, the distribution is dividedinto hundreds (100 classes). But the distribution can be divided intoanother arbitrary number of classes. To eliminate any aberrant lobes 28,29 due to the noise, the invention only processes part of the curve 70between the respective ordinate points X₁ and (100−X′₁). In a preferredembodiment: X₁=X′₁=5%. But the values of X₁ and X′₁ can beparameterized; i.e. can take other values (percentage), and not be equalto one another.

A third assumption of implementation of the invention process consistsin considering that the optical density change corresponding to thecolor alteration takes place according to a linear model, characterizedfor example by a first equation Eq (1) of the type: D_(F)=αD_(R)+β.

The preferred embodiment of the invention uses the linear model byapplying it to the optical densities of pixels of strips 18 of thedigital image 12. In another embodiment, this linear model can also beused by applying it to the color intensities.

In the equation D_(F)=αD_(R)+β, D_(F) represents the optical densityencoded value of an altered pixel, i.e. a pixel whose optical densityencoded value has for example decreased with regard to the referenceoptical density encoded value D_(R) of said pixel. The reference opticaldensity encoded value D_(R) is the optical density of the original colorof the point corresponding spatially to the pixel of the digital image12 in the plane of the silver image 3. The values of α and β varyaccording to the main axis 19 of the digital image 12.

A fourth assumption prior to the implementation of the process of theinvention, acknowledges that the actual color degradation profile of theimage varies continuously (i.e. without break), smooth (i.e. with a slowvariation) and monotonic (i.e. with degradation always decreasing fromthe edge towards the point of least degradation). The point of leastdegradation of the image 12 is represented for example by the point 20placed in the center of the image 12. But this point of leastdegradation can be placed spatially anywhere in the plane of the image12. The objective of the detected degradation profile is to approach theactual degradation profile. Thus, the result of color restoration is allthe better as the degradation profile detected by the process of theinvention is continuous, smooth, and monotonic. That is that the profileis free from the chromatic variations inherent to the contents of theimage. Filtering means known to those skilled in the art, enable thedetected degradation profile to be made continuous, smooth andmonotonic.

In a preferred embodiment of the invention, the steps of detection ofimage color alteration are generally preceded by the automatic initialfiltering of all the pixels of the digital image 12. The initialfiltering enables the influence of the contents of the image and thedust (artifacts in the image) to be minimized. But, another particularembodiment enables not performing this initial filtering. The digitalimage 12 is filtered by using mathematical morphology operators known tothose skilled in the art. For each pixel of the image 12, an opening(erosion followed by a dilation) is performed, then a closing (dilationfollowed by an erosion), by using a structuring element having forexample a square shape and containing 9 or 25 pixels. This opening andclosing can be performed successively n times, n being an integer.

The process of the invention enables the automatic division of thedigital image 12 into pixel strips 18 arranged perpendicular to thedirection of the main axis 19 of the image according to which the coloralteration occurs. The joining of all the pixels of each strip 18represents all the pixels of the image 12. The image 12 is divided intopixel strips 18 according to the adjacent parallel strips 18; accordingto a first embodiment, these adjacent parallel strips have no commonpixel between them, or according to a second embodiment, the image isdivided according to parallel strips partially overlapping by twosaccording to at least one row of pixels; a third embodiment enables theimage to be divided at the same time into adjacent or overlappingstrips. The embodiment selected from among these three variants dependson the algorithm used to displace, in the image 12, the moving strip 18of width 21. In a preferred embodiment, the strips 18 have the samewidth 21. But the algorithm implementing the process of the inventionalso enables uneven strips 18 of widths 21 to be selected.

Based on the division of the digital image 12 into pixel strips 18, theprocess of the invention enables the automatic calculation, for eachpixel strip 18, and according to FIG. 6, for each of the planes of thecolored channels 40, 50, 60 forming the image 12 (e.g. the red, greenand blue channels), of an optical density distribution of each pixel ofsaid strip 18. An example of the optical density distribution is shownin FIG. 4.

The determination of the spatial variations of the color alteration inthe entire image 12, and for each of the color channels, e.g. red, greenand blue, consists in separating or in filtering the contribution of theimage contents, from the contribution of the color alteration. This bytaking into account the variation of the distribution of the opticaldensity encoded values, as shown in FIG. 4.

FIG. 5 shows, for one color channel of the image, a spatialrepresentation of the actual optical density distribution in theextension Xe of said image. The extension Xe represents the dimension ofthe image according to which the color alteration or degradation occurs(main axis 19). The lines 41 and 45 correspond to the edges of theimage. The actual optical density distribution is represented forexample by curves 30, 31, 32, 33, 34. These curves 30, 31, 32, 33, 34correspond to a mixing of the color degradation profile and contents ofthe image. The process of the invention enables the automatic separationof the signals linked to the image contents on the one hand, and to thecolor degradation profile on the other hand.

According to FIG. 5, the process of the invention enables the automaticcalculation, for each of the optical density distributions of the pixelsof the pixel strip 44, of a top crude reference value of optical density36, and a bottom crude reference value of optical density 37. Accordingto FIG. 5, the optical density distribution is represented by a familyof curves 30, 31, 32, 33, 34. The curves 30 and 34 represent for examplethe optical density curves of the maximum and the minimum of thedistribution respectively. In a preferred embodiment, the algorithm ofthe process of the invention automatically eliminates these two extremesof the distribution (curves 30 and 34) to perform the calculations. Thetop 36 and bottom 37 crude reference values are calculated from thecurves 31 and 32 which correspond for example respectively to theoptical density curves of the family of curves placed in thedistribution, in the neighborhood respectively of the end curves 30 and34.

However, in another embodiment, the top crude reference values ofoptical density 39, and bottom 38, are calculated from the opticaldensity curves of the maximum 30 and the minimum 34.

Based on the top 36 and bottom 37 crude reference values of opticaldensity, the process of the invention enables the top 46 and bottom 47filtered reference values of optical density to be calculated.

The process of the invention, based on the filtered reference values 46,47, automatically determines the optical density reference curves: theoptical density top reference curve 42, and the optical density bottomreference curve 43. The optical density reference curves 42, 43 arerepresentative of the color degradation profile of the image. Thesereference curves 42, 43 are obtained by filtering, by taking intoaccount the fourth assumption linked to the implementation of theinvention. Fourth assumption is based on a color degradation profile ofthe image that varies in a continuous, smooth, and monotonic way. In apreferred embodiment, the filtering operation, whose principle isrepresented in FIG. 9, is performed so as to apply this fourthassumption, to eliminate the end points of the correspondingdistribution, after filtering, to the end curves of the distribution C₀and C₁₀₀, and to separate the image contents from the color degradationprofile of said image. The curves C₀ and C₁₀₀ are the curves of the topand bottom optical density reference that represent the end curves ofthe distribution.

According to FIG. 9 and in the preferred embodiment of the invention,the filtering operation is performed by using the “following the maxima”method. This filtering method means, from a curve 31 representative of adistribution, obtaining the resultant curve that represents the minimumof the two curves 35C and 36C. This enables the dips of the initialcurve 31 to be eliminated and thus the monotonic assumption to berespected. According to FIG. 6, for each of the color channels 40, 50,60 forming the image, the top filtered reference values of opticaldensity 46, 56, 66, and the bottom filtered reference values of opticaldensity 47, 57, 67, are calculated based on the use of a filtering ofthe image 12 by the “following the maxima” method in each pixel strip18.

According to FIGS. 6 and 10, the process of the invention thus enables,after filtering, smoothed corrected curves 42, 43, 52, 53, 62, 63 to beobtained. According to a preferred embodiment, the curves C₀ and C₁₀₀,corresponding to the ends of the distribution (0% and 100%), wereexcluded. FIG. 6 represents the top reference curves of optical density42, 52, 62 and bottom 43, 53, 63 respectively. Said reference curvesbeing represented in each plane 40, 50, 60 corresponding to the colorchannels. By analogy with the graphic representation of FIG. 3, theimage extension by which the variation of color alteration occurs isrepresented in abscissa in FIG. 6 by the distance between the lines 41and 45 for the color channel 40, between lines 45 and 55 for the colorchannel 50, and between lines 55 and 65 for the color channel 60. TheY-axis of FIG. 6 represents the optical density encoded valuesV_(C)(DO). The photographic emulsion layer of the image 3 correspondingto the color red is represented in abscissa for example by the plane 40of the image; the photographic emulsion layer corresponding to the colorgreen is represented in abscissa for example by the plane 50 of theimage; the photographic emulsion layer corresponding to the color blueis represented in abscissa for example by the plane 60 of the image.According to FIG. 6, the process of the invention enables the automaticdetermination, for each of the color channels 40, 50, 60 forming theimage, and based on the maximum value of optical density 46M, 56M, 66Mof the top reference curve of optical density, of the pixel strip ofleast degradation 44M, 54M, 64M. The top filtered reference values ofoptical density of the pixel strips of least degradation 44M, 54M, 64Mare respectively 46M, 56M, 66M. The bottom filtered reference values ofoptical density of the pixel strips of least degradation 44M, 54M, 64Mare respectively 47M, 57M, 67M. This pixel strip of least degradationcorresponds to the pixel strip of the image having undergone a minimumalteration or degradation of color. According to a particular embodimentof the process of the invention, the strip of least degradation is thepixel strip comprising a single row of pixels, and passing through thecenter 20 of the image 12.

FIG. 7 represents the optical density restoration function. The lineartransformation is performed according to a transformation equation Eq(2)of the type:D_(R)=a D_(F)+b;

-   -   equation where a and b are independent for each colored channel,        red (a_(r), b_(r)), green (a_(g), b_(g)), blue (a_(b), b_(b)),        and in which a and b are determined by the algorithm enabling        the process of the invention to be implemented. This second        equation Eq(2) represents the reverse transformation of that of        the first equation Eq(1). The simultaneous application of the        equation Eq(2) in three colored channels is expressed as:        D _(Rr) =a _(r) D _(Fr) +b _(r)        D _(Rg) =a _(g) D _(Fg) +b _(g)        D _(Rb) =a _(b) D _(Fb) +b _(b)        or, as a matrix: ${\begin{matrix}        D_{Rr} \\        D_{Rg} \\        D_{Rb}        \end{matrix}} = {{{\begin{matrix}        a_{r} & 0 & 0 \\        0 & a_{g} & 0 \\        0 & 0 & a_{b}        \end{matrix}}\quad{\begin{matrix}        D_{Fr} \\        D_{Fg} \\        D_{Fb}        \end{matrix}}} + {\begin{matrix}        b_{r} \\        b_{g} \\        b_{b}        \end{matrix}}}$

In a particular embodiment of the invention, the non-diagonal terms ofthe three-row, three-column matrix, can be not zero to take into accountthe spectral overlapping effect of absorption, as describes for examplein the above-mentioned U.S. Pat. No. 5,796,874.

According to FIGS. 6, 7 and 10, the process of the invention thenenables for each pixel strip 44, 54, 64 of the digital image other thanthe pixel strip of least degradation 44M, 54M, 64M, and for each of thecolor channels forming the image, the application of a lineartransformation enabling the transformation of the optical densityfiltered values 46, 56, 66 placed on the top reference curve of opticaldensity 42, 52, 62 and the optical density filtered values 47, 57, 67placed on the bottom reference curve of optical density 43, 53, 63 ofsaid each pixel strip 44, 54, 64, respectively into top 46M, 56M, 66Mand bottom 47M, 57M, 67M values of optical density of the pixel strip ofleast degradation 44M, 54M, 64M.

The process of the invention thus enables a digital image 12 to beobtained automatically whose colors are restored, i.e. whose colors weretransformed to correspond with those of the original silver image. Theoperator can for example, having applied the process of the invention toan altered image, display the digital image 12 whose colors arerestored, on the screen 11; they can also then reproduce this restoredimage, for example on paper by using a laser or ink jet printer, or onphotographic film.

While the invention has been described with reference in particular toits preferred embodiments, it is apparent that variants andmodifications can be produced within the scope of the claims.

1. An automatic process of color restoration of a silver image whosecolor is altered with regard to an original color of said silver imagethe color alteration not occurring evenly, spatially in the plane of theimage, and according to a direction parallel to one main axis of theimage; said process comprises the steps of: a) digitizing the alteredsilver image by using a measuring scale of optical densities to create adigital image; b) filtering all pixels of the digital image; c) dividingthe digital image into pixel strips arranged perpendicular to adirection of a main axis of the image according to which the coloralteration occurs, a joining of all the pixels of each striprepresenting all the pixels of the digital image; d) calculating foreach pixel strip, and for each of color channels forming the image, adistribution of optical densities of the pixels forming said strip; e)calculating for each of said distributions of said step d), a top crudereference value of optical density, and a bottom crude reference valueof optical density; f) calculating from all the top and bottom crudereference values of said step e), respectively corresponding topfiltered reference values of optical density and bottom filteredreference values of optical density; g) determining from the top andbottom filtered reference values of optical density of said step f),respectively top reference curves of optical density and bottomreference curves of optical density, said reference curves beingrepresentative of a color degradation profile of the image; h)determining for each of the color channels forming the image, and from amaximum value of optical density of the top reference curve of opticaldensity, a pixel strip of least degradation; i) applying to each pixelstrip of the digital image other than the pixel strip of leastdegradation, and to each of the color channels forming the image, alinear transformation enabling a transformation of the optical densityfiltered values placed on the top reference curve and on the bottomreference curve of optical density of said each pixel strip,respectively into top and bottom values of optical density of the pixelstrip of least degradation.
 2. The process according to claim 1, whereinan initial filtering of the altered digital image is performed by usingmathematical morphology operators of the type order opening (n) followedby order closing (n), with (n) being an integer.
 3. The processaccording to claims 1, wherein the top filtered reference values ofoptical density, and the bottom filtered reference values of opticaldensity, are calculated by using a filtering of the image by the methodof following a maxima in each pixel strip.
 4. The process according toclaims 1, wherein the digital image is divided into pixel stripsaccording to adjacent parallel strips having no common pixel betweenthem.
 5. The process according to claim 1, wherein the digital image isdivided into pixel strips according to parallel strips partiallyoverlapping by twos according to at least one row of pixels.
 6. Theprocess according to claim 1, wherein the top and bottom crude referencevalues of optical density correspond respectively to the optical densitydistribution curves placed in a neighborhood of maximum and minimumoptical density curves of said distribution.
 7. The process according toclaim 1, wherein the top and bottom crude reference values of opticaldensity correspond respectively to a maximum and minimum optical densitydistribution curves of said distribution.
 8. The process according toclaim 1, wherein the strip of least degradation is a pixel strip of theimage comprising the pixel of maximum optical density value of the topreference curve of optical density.
 9. The process according to claim 1,wherein the strip of least degradation is the pixel strip comprising asingle row of pixels, said strip passing through a center of the image.10. The process according to claim 1, wherein the planes of the colorchannels forming the image are the red, green and blue ones.